The guts of the <code>ICLUST</code> algorithm. Called by <code>ICLUST</code> See ICLUST for description.

ICLUST.cluster

A general purpose toolbox developed originally for personality, psychometric theory and experimental psychology. Functions are primarily for multivariate analysis and scale construction using factor analysis, principal component analysis, cluster analysis and reliability analysis, although others provide basic descriptive statistics. Item Response Theory is done using factor analysis of tetrachoric and polychoric correlations. Functions for analyzing data at multiple levels include within and between group statistics, including correlations and factor analysis. Validation and cross validation of scales developed using basic machine learning algorithms are provided, as are functions for simulating and testing particular item and test structures. Several functions serve as a useful front end for structural equation modeling. Graphical displays of path diagrams, including mediation models, factor analysis and structural equation models are created using basic graphics. Some of the functions are written to support a book on psychometric theory as well as publications in personality research. For more information, see the <https://personality-project.org/r/> web page.

William Revelle

psych

Procedures for Psychological, Psychometric, and Personality
Research

ICLUST.cluster function

Function to form hierarchical cluster analysis of items — ICLUST.cluster

<dl>

 <dt>r.mat</dt>
<dd>A correlation matrix</dd>

 <dt>ICLUST.options</dt>
<dd>A list of options (see <code>ICLUST</code>)</dd>

 <dt>smc.items</dt>
<dd>passed from the main program to speed up processing</dd>

</dl>

ICLUST.cluster: Function to form hierarchical cluster analysis of items

Description

Usage

Arguments

Value

Details

References

See Also